Existing approaches to resource allocation in a virtualized computing environment are typically based on relatively static and/or coarse-grained decisions about the expected workload to be processed within the virtualized computing environment. A virtualized computing environment typically includes multiple physical computing systems that each include a hypervisor, virtual machine monitor, or similar logic that is configured to manage the concurrent execution of multiple virtual machines. Each virtual machine may have a distinct guest operating system and corresponding applications.
When a virtual machine is created, it may be assigned or given access to some portion of the physical resources of its host physical computing system. Typically, the amount of physical resources (e.g., CPU or memory) is determined when the virtual machine is defined or instantiated, and not changed or modified during the active lifetime of the virtual machine. Such an approach may be lead to some resources being unavailable to time-sensitive user activities, hindering the performance of virtual machines that need resources for more important activities.
In addition, decisions regarding the amount of physical resources to assign or provide to a virtual machine are often made on an ad hoc basis or otherwise based on inaccurate or outdated information. For example, many organizations simply utilize a “one size fits all” approach to resource allocation, and provide a uniform resource set for virtual machines allocated for different users or uses. Such uniform allocation, while simple and seemingly fair, does not consider the actual computing needs of those users, which may vary dramatically based on differing roles, projects, or even time of day. Such uniform allocation decisions may result in a collection of virtual machines that may not be closely matched to their actual computing requirements, in that some virtual machines do not have sufficient resources, while others are allocated excess resources based on the low priority tasks they are executing.
Typically, the above issues are addressed by providing every virtual machine with substantial excess computing capacity, in order to minimize user frustration due to under-resourced virtual machines. Of course, while this approach may reduce user frustration for high-need users, it allows virtual machines executing low priority activities to consume critical resources during periods of high demand, causing performance degradation for other important users or processes.